Differences between single-cell transcriptomes may someday help explain enhanced human cognitive function. Scientists recently developed transcriptomic catalogues to help identify human-specific regulatory genes.
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Some 9.3 million to 6.5 million years ago humans evolved from apes.1 Gradual development of enhanced cognitive function has enabled humans to impact natural history in a manner no other species has been capable of. Now, Suresh et. al is trying to better understand the evolutionary mechanisms responsible for human cognition.2 Research preceding Suresh et. al indicated that the complexity of humans’ cerebral cortex was responsible for improved cognitive function in humans as compared to other animals.3 From an evolutionary perspective, it was suspected that the mechanisms underlying humans’ enhanced cognitive function stemmed from differences in the regulation of gene expression.4
In order to characterize these differences, Suresh et. al utilized a dataset of gene expression created by the BRAIN Initiative Cell Census Network.5 This dataset was compiled through a biological technique known as single-nucleus RNA sequencing (snRNA-seq). snRNA-seq is like scRNA-seq (single-cell RNA sequencing), except for the fact that it only sequences the RNA present in the nuclei of cells and is typically reserved for cell types that are more difficult to sequence through scRNA-seq.6 Like scRNA-seq, snRNA-seq sequences the transcriptome of the cells of interest. In other words, genetic information, DNA, is transcribed into RNA and then sequenced by snRNA-seq. By sequencing a nuclei’s RNA, researchers are able to identify cell types, quantify gene expression, or understand gene regulation within different cell types, among other things. The dataset from BRAIN Initiative Cell Census Network included single-nucleus transcriptomes from the middle temporal gyrus (MTG) of five primates (human, chimp, gorilla, macaque, and marmoset). By observing the snRNA-seq data and utilizing a computer program called MetaNeighbor, Suresh et. al was able to distinguish 57 homologous cell types with similar expression (cells with similar function and or genes that derived from a common ancestor), in addition to a few differences in expression between humans and non-human primates in one or more cell types. The similar expression indicated conserved transcriptional profiles across primates, while the differences indicated divergent expression, potentially responsible for the differences observed in cognitive function.
Moving forward, Suresh et. al wanted to study the cell types shared across species to understand how their gene expression patterns compare. To do this, they calculated expressolog scores to measure gene functional conservation of their 57 homologous cell types across species. These scores indicated evolutionary differences between humans and non-human primates. Additionally, they found that orthologous genes (genes that originated in separate species as a result of speciation) within the respective cell types had similar patterns of expression across cell type. These findings influenced the researchers to explore the functional impact of the observed differences by using gene co-expression networks (observing gene expression correlations across species). They believed that genes with variant expression in humans as compared to non-human primates would experience greater changes in their co-expression networks.
In order to study co-expression, they limited their list of genes to a number of human genes that had orthologs in the non-human primates, excluded lowly expressed genes, selected genes with low expressolog scores (an indicator of expression divergence), and then observed their co-expression conservation scores across 18 animals. They were able to narrow their list to 139 putative novel regulatory genes, several of which were responsible for brain disorders. They found that the 139 genes were younger, had higher GC content, and had increased cell type-specific expression, indicating that they would have had to of evolved under mild evolutionary constraints. Additionally, these genes experienced expression and connectivity patterns specific to humans. While the authors cannot conclude that these genes are responsible for enhanced cognitive function, they are certainly genes of interest for future study. One of the 139 genes that they identified, NHEJ1, is a DNA repair gene that is suspected of having undergone rapid evolution, subsequently contributing to regulatory divergence in humans.
Suresh et. al’s framework of identifying genes with cell type-specific expression and gene co-expression will prove useful to scientists as it can help further elucidate cell-types and genes that have played prominent roles within evolution. Furthermore, Suresh et. al created a website for their single-cell gene expression and co-expression data for users to explore. Their future explorations should include developing more brain specific co-expression networks. The co-expression networks developed for the 19 animals in their co-expression analysis were not brain specific. Additional research should also involve identifying cell types unique to a single species. Increased understanding of cellular or genetic differences of any kind can lend further insight into evolution.
References
1.) Almécija S., A. S. Hammond, N. E. Thompson, K. D. Pugh, S. Moyà-Solà, et al., 2021 Fossil apes and human evolution. Science 372: eabb4363. https://doi.org/10.1126/science.abb4363
2.) Suresh H., M. Crow, N. Jorstad, R. Hodge, E. Lein, et al., 2023 Comparative single-cell transcriptomic analysis of primate brains highlights human-specific regulatory evolution. Nature Ecology & Evolution 7: 1930–1943. https://doi.org/10.1038/s41559-023-02186-7
3.) Hodge R. D., T. E. Bakken, J. A. Miller, K. A. Smith, E. R. Barkan, et al., 2019 Conserved cell types with divergent features in human versus mouse cortex. Nature 573: 61–68. https://doi.org/10.1038/s41586-019-1506-7
4.) King M.-C., and A. C. Wilson, 1975 Evolution at Two Levels in Humans and Chimpanzees. Science 188: 107–116. http://www.jstor.org.proxy048.nclive.org/stable/1739875
5.) Jorstad N. L., J. H. T. Song, D. Exposito-Alonso, H. Suresh, N. Castro-Pacheco, et al., 2023 Comparative transcriptomics reveals human-specific cortical features. Science 382: eade9516. https://doi.org/10.1126/science.ade9516
6.) Atha B., 2023 Single-Cell RNA Sequencing vs Single-Nucleus RNA Sequencing. https://www.biocompare.com/Editorial-Articles/609591-Single-Cell-RNA-Sequencing-vs-Single-Nucleus-RNA-Sequencing/
Author information:
Josh Merva – jomerva@davidson.edu
Davidson College Class of 2025
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Department of Biology, Davidson College, Davidson, NC 28036
Thank you for your article, it was concise yet communicated the general methodology of the experiment well. I was curious about the usage of the new technique you mentioned (snRNA-seq) and its distinction from scRNA-seq. Since the MTG is unique to humans, I was left wondering what unique characteristics in its cellular composition necessitated this new technique? Every time that I learn of a new sequencing technique, I can not help but wonder what new kinds of questions it can help answer. Finally, the way that genomics can help us answer both historical questions and simultaneously be paving the way for the future of medicine is truly amazing.
I really enjoyed reading your article. It caught my attention early on because thinking of how we have been the only species to evolve such high cognition fascinates me. I have always thought this topic is often overlooked but very important. Additionally, the simple wording and lay-term explanations of complex concepts went a long way in keeping me engaged. I find it very interesting that the researchers chose to sequence nuclei rather than entire cells. Both the reasoning behind this choice and more information on how exactly the method works. I do understand the exclusion of these explanations as they are probably beyond the scope of a News and Views article. I hope more of this research is done as I think the findings could also provide very important information about brain function and brain disorders.
I really enjoyed reading your article. It caught my attention early on because thinking of how we have been the only species to evolve such high cognition fascinates me. I have always thought this topic is often overlooked but very important. Additionally, the simple wording and lay-term explanations of complex concepts went a long way in keeping me engaged. I find it very interesting that the researchers chose to sequence nuclei rather than entire cells. Both the reasoning behind this choice and more information on how exactly the method works. I do understand the exclusion of these explanations as they are probably beyond the scope of a News and Views article. I hope more of this research is done as I think the findings could also provide very important information about brain function and brain disorders. Great article!
I really enjoyed reading your article. It caught my attention early on because thinking of how we have been the only species to evolve such high cognition fascinates me. I have always thought this topic is often overlooked but very important. Additionally, the simple wording and lay-term explanations of complex concepts went a long way in keeping me engaged. I find it very interesting that the researchers chose to sequence nuclei rather than entire cells. Both the reasoning behind this choice and more information on how exactly the method works. I do understand the exclusion of these explanations as they are probably beyond the scope of a News and Views article. I hope more of this research is done as I think the findings could also provide very important information about brain function and brain disorders. Great article!!
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